New Online EM Algorithms for General Hidden Markov Models. Application to the SLAM Problem. - Sylvain Le Corff; Gersende Fort; Eric Moulines (LVA/ICA, 2012)

Online EM for indoor simultaneous localization and mapping. - Thierry Dumont; Sylvain Le Corff (ICASSP, 2013)

Convergence of a Particle-Based Approximation of the Block Online Expectation Maximization Algorithm. - Sylvain Le Corff; Gersende Fort (ACM Trans. Model. Comput. Simul., 2013)

Simultaneous localization and mapping in wireless sensor networks. - Thierry Dumont; Sylvain Le Corff (Signal Process., 2014)

A Shrinkage-Thresholding Metropolis Adjusted Langevin Algorithm for Bayesian Variable Selection. - Amandine Schreck; Gersende Fort; Sylvain Le Corff; Eric Moulines (IEEE J. Sel. Top. Signal Process., 2016)

Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models. - Ngoc Minh Nguyen; Sylvain Le Corff; Eric Moulines (EURASIP J. Adv. Signal Process., 2017)

Optimal scaling of the random walk Metropolis algorithm under L p mean differentiability. - Alain Durmus; Sylvain Le Corff; Eric Moulines; Gareth O. Roberts (J. Appl. Probab., 2017)

Consistent Estimation of the Filtering and Marginal Smoothing Distributions in Nonparametric Hidden Markov Models. - Yohann de Castro; Elisabeth Gassiat; Sylvain Le Corff (IEEE Trans. Inf. Theory, 2017)

Optimizing Thermal Comfort and Energy Consumption in a Large Building without Renovation Work. - Sylvain Le Corff; Alain Champagne; Maurice Charbit; Gilles Nozière; Eric Moulines (DSW, 2018)

Online sequential Monte Carlo smoother for partially observed diffusion processes. - Pierre Gloaguen; Marie-Pierre Étienne; Sylvain Le Corff (EURASIP J. Adv. Signal Process., 2018)

End-to-end deep metamodeling to calibrate and optimize energy loads. - Max Cohen; Maurice Charbit; Sylvain Le Corff; Marius Preda; Gilles Nozière (CoRR, 2020)

The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction. - Alice Martin 001; Charles Ollion; Florian Strub; Sylvain Le Corff; Olivier Pietquin (CoRR, 2020)

Identifiability and Consistent Estimation of Nonparametric Translation Hidden Markov Models with General State Space. - Elisabeth Gassiat; Sylvain Le Corff; Luc Lehéricy (J. Mach. Learn. Res., 2020)

Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA. - Hermanni Hälvä; Sylvain Le Corff; Luc Lehéricy; Jonathan So; Yongjie Zhu; Elisabeth Gassiat; Aapo Hyvärinen (NeurIPS, 2021)

NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform. - Achille Thin; Yazid Janati El Idrissi; Sylvain Le Corff; Charles Ollion; Eric Moulines; Arnaud Doucet; Alain Durmus; Christian X. Robert (NeurIPS, 2021)

Joint self-supervised blind denoising and noise estimation. - Jean Ollion; Charles Ollion; Elisabeth Gassiat; Luc Lehéricy; Sylvain Le Corff (CoRR, 2021)

End-to-end deep meta modelling to calibrate and optimize energy consumption and comfort. - Max Cohen; Sylvain Le Corff; Maurice Charbit; Marius Preda; Gilles Nozière (CoRR, 2021)

Learning Natural Language Generation from Scratch. - Alice Martin 001; Guillaume Quispe; Charles Ollion; Sylvain Le Corff; Florian Strub; Olivier Pietquin (CoRR, 2021)

Diffusion bridges vector quantized variational autoencoders. - Max Cohen; Guillaume Quispe; Sylvain Le Corff; Charles Ollion; Eric Moulines (ICML, 2022)

Learning Natural Language Generation with Truncated Reinforcement Learning. - Alice Martin 001; Guillaume Quispe; Charles Ollion; Sylvain Le Corff; Florian Strub; Olivier Pietquin (NAACL-HLT, 2022)

State and parameter learning with PARIS particle Gibbs. - Gabriel Cardoso 001; Yazid Janati El Idrissi; Sylvain Le Corff; Eric Moulines; Jimmy Olsson (ICML, 2023)

Monte Carlo guided Diffusion for Bayesian linear inverse problems. - Gabriel Cardoso 001; Yazid Janati El Idrissi; Sylvain Le Corff; Eric Moulines (CoRR, 2023)

Backward Importance Sampling for Online Estimation of State Space Models. - Alice Martin 001; Marie-Pierre Étienne; Pierre Gloaguen; Sylvain Le Corff; Jimmy Olsson (J. Comput. Graph. Stat., 2023)

HERMES: Hybrid Error-corrector Model with inclusion of External Signals for nonstationary fashion time series. - Etienne David; Jean Bellot; Sylvain Le Corff (Trans. Mach. Learn. Res., 2023)

Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems. - Gabriel Cardoso 001; Yazid Janati El Idrissi; Sylvain Le Corff; Eric Moulines (ICLR, 2024)

Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation. - Sobihan Surendran; Adeline Fermanian; Antoine Godichon-Baggioni; Sylvain Le Corff (NeurIPS, 2024)

Diffusion posterior sampling for simulation-based inference in tall data settings. - Julia Linhart; Gabriel Victorino Cardoso; Alexandre Gramfort; Sylvain Le Corff; Pedro L. C. Rodrigues (CoRR, 2024)

Variational quantization for state space models. - Etienne David; Jean Bellot; Sylvain Le Corff (CoRR, 2024)

Additive smoothing error in backward variational inference for general state-space models. - Mathis Chagneux; Elisabeth Gassiat; Pierre Gloaguen; Sylvain Le Corff (J. Mach. Learn. Res., 2024)

Variational excess risk bound for general state space models. - Elisabeth Gassiat; Sylvain Le Corff (Trans. Mach. Learn. Res., 2024)

Identifiability of discrete input-output hidden Markov models with external signals. - Etienne David; Jean Bellot; Sylvain Le Corff; Luc Lehéricy (Stat. Comput., 2024)

Theoretical Convergence Guarantees for Variational Autoencoders. - Sobihan Surendran; Antoine Godichon-Baggioni; Sylvain Le Corff (AISTATS, 2025)

An analysis of the noise schedule for score-based generative models. - Stanislas Strasman; Antonio Ocello; Claire Boyer; Sylvain Le Corff; Vincent Lemaire 002 (Trans. Mach. Learn. Res., 2025)

Latent Guided Sampling for Combinatorial Optimization. - Sobihan Surendran; Adeline Fermanian; Sylvain Le Corff (CoRR, 2025)

Tree-based variational inference for Poisson log-normal models. - Alexandre Chaussard; Anna Bonnet; Elisabeth Gassiat; Sylvain Le Corff (Stat. Comput., 2025)